In a world where the patient visits the doctor across a telemedicine system to get advice, and sometimes a prescription, there are many opportunities for the IoT to lend a hand. Maybe the household scale is automatically sending weight trends to the physician’s screen, as are the nutrition tracker that picks up some food details from NFC chips or scanned barcodes, and the activity trackers on the smartwatch, smartphone, and fitness band which have all consolidated their data, deduped it based on timecodes, and created an overall activity profile. On top of these lifestyle data points are prescription adherence data based on bottle opens or stomach acid detection or biometric data such as glucose levels for diabetics. Many other devices are available of course from cups that detect their contents to desktop blood analyzers to ambitious medical tricorders (yes, from Star Trek).

These data aren’t presented to the doctor as giant spreadsheets of raw numbers, instead the devices themselves attempt to reconcile the myriad measurements. For example, the health and fitness devices may try to balance calories in with calories burned and then check the weight trend to see if predicted weight change is realized, and if not, where the problem might be. These systems can then choose to coach the patient on activities such as more diligent food entry or more consistent tracker use. More healthcare related activities might be the adherence tools linking their data with biometrics such as blood pressure or glucose levels. Again, these data aren’t dumped directly on the physician because that would simply result in a lack of engagement and probably a request to never see them again. Instead they are consolidated into clear overviews where the physician can dig down if necessary or simply integrate them into the patient’s treatment regimen if not.

In this world where so much data is being shared “beneath the surface” of the patient / physician interaction there are more opportunities than ever for helping with the conversation. During these interactions there will be little tolerance for TV ads or other invasive messaging but there will be a strong appetite for just-in-time training for both the physician and patient. Types of content that might be welcome here are product details including common risks, dosing details, and expected results. More advanced information types can even be patient coaching in-channel with both the physician and patient sharing a screen – think of DrawMD but over WebEx.

IoT for Healthcare

Now is the time to be thinking of these channels even though they are some years off from mass acceptance. A recent research paper from Altimeter Group looks at the IoT from a customer experience standpoint and provides a nice model for thinking of how we can integrate healthcare into the mix. That document organizes the customer experience in IoT into five buckets each containing multiple use cases:

Use cases diagram from Altimeter Group report: Customer Experience in the Internet of Things

For each grouping, we can imagine many healthcare opportunities. Some might be:

Reward

The obvious angle here is adherence with rewards coming from both intrinsic and extrinsic motivations.

Intrinsic motivations are sometimes described as RAMP: Relatedness, Autonomy, Mastery, and Purpose and game strategies can use these motivations to propel users to higher engagement. The IoT data that is coming available simply provides orders of magnitude more opportunities to use game design elements to help patients engage.

Extrinsic motivations are fairly obvious and are usually connected to the insurance industry through reward systems such as those promoted by HealthPrize or other systems. There is a place for extrinsic motivation from pharmaceutical companies too – tieing copay opportunities to adherence data is only the most obvious way to use the data from IoT devices, there are certainly more ways to reward patients for their adherence and better health.

Information & Decision Making

Evaluation and tracking opportunities abound in healthcare, but of course we need to make sure we follow the right channels through the FDA’s regulatory regime. Some of the most valuable uses of IoT will require FDA certifications but it is likely that the first movers here will enjoy an advantage, as long as they leverage it and keep pushing. Being first and then sitting back while the competition leapfrogs the new technology is not helpful for the healthcare company or the early adopter patients.

Facilitation

The smoothing of processes and decisions for patients can tie into IoT but marketers need to worry about the same FDA regulations here as above. There are opportunities here but maybe not the low-hanging fruit that the other use case groups provide.

Service

Here, integration with the call center, especially for those brands that already provide nurse support over the phone, could really leverage the IoT ecosystem. Image a coaching service provided to patients that allows for data sharing from connected devices such as the aforementioned glucose monitors or adherence tools. Such a system could provide much more specialized and targeted advice to patients and still retain the personal touch of the nurse, especially if the connection was over a video link like Facetime or Skype.

Innovation

Here, we are looking at the “beyond the pill” options for healthcare companies. Integration of IoT into the core product, such as being seen in the diabetes market with Sanofi’s iBGStar and Dexcom’s Share system, will provide opportunities for healthcare companies to expand their product benefits and, hopefully, get more leverage with payors in the healthcare system.

The Road Forward

A recent report from the FTC looks at the healthcare angle of IoT extensively and is a must-read for anyone starting to think about the opportunities here. It may seem “blue-sky” but it’s already here in small ways. As the famous quote by William Gibson states, “The future is already here – it’s just not evenly distributed.”

]]>http://www.klick.com/health/news/blog/mhealth/the-internet-of-things-in-healthcare/feed/0Social listening shootout: Sysomos vs. Crimson Hexagonhttp://www.klick.com/health/news/blog/social/social-listening-shootout-sysomos-vs-crimson-hexagon/
http://www.klick.com/health/news/blog/social/social-listening-shootout-sysomos-vs-crimson-hexagon/#commentsThu, 26 Feb 2015 22:39:50 +0000http://www.klick.com/health/?p=369972These types of comparisons can be a bit difficult because I have a lot of experience with Sysomos, having conducted over 20 different listening engagements on the tool whereas Crimson Hexagon I was learning over a month on one engagement. I’ve tried not to allow the newness of Crimson Hexagon or the familiarity with Sysomos color my review but I suspect that it will be inevitable at some level.

Data

The fundamental requirement of any social listening tool is to have access to the data. Both Sysomos and Crimson Hexagon have access to billions of social media posts. 456.1 billion on Sysomos as of this writing and over 500 on Crimson Hexagon (actually soon to be 700 billion) according to their blog post.

How do they differ?

So, both platforms have a lot of data to draw on, but how do they differ? They follow somewhat different channels.

Sysomos

Crimson Hexagon

Analysis

Twitter

Twitter

Both have access to the Twitter fire hose but Sysomos goes back only two years while CH goes back at least to December 2009

Facebook

Facebook

Both have access to public Facebook data but because of terms of use only see public pages

Blogs

Blogs

Both have full text of large numbers of blogs available for searching

Forums

Forums

Both have full text of large numbers of forums available for searching and both can add new forums if required

News

News

Both index numerous news sites and give an idea of the number of news stories on the topic

Google+

Google+

Both index the public information on this source, such as it is

Instagram Posts

Instagram Hashtags

Sysomos indexes all Instagram posts and stores them just like other channels, CH only indexes content that contains defined hashtags and only indexes it going forward

YouTube

YouTube

Video descriptions and comments are stored for searching

Product Reviews

In our test we only saw reviews from Amazon but other sources are most likely available. For Healthcare this isn’t a super-relevant source but it’s interesting to see what shows up in the long tail of product reviews.

Google Pages

Indexes only specified pages by using a linked account

Facebook Pages

Indexes only specified pages by using a linked account

Weibo

Unavailable during our test and we’re not fluent in Mandarin anyway.

Flickr

Sysomos indexes the text surrounding Flickr images, similar to Instagram

Other Video Sites

Shows videos from other sites such as Daily Motion

Tumblr

Indexes Tumblr feeds similarly to blogs or Twitter posts

Sysomos also provides access to LinkedIn and Wikipedia but we don’t put those sources into the “data” category because the individual posts aren’t stored, they only allow the user to get a small dashboard on a company page or Wikipedia entry.

Winner: Tie

When looking at data sources it’s hard to pick a winner. Both tools cover the basics, of course, but the differences are essentially equally compelling. This one is a tie.

Crimson Hexagon has the advantage of having Twitter data back to the Pliocene era whereas Sysomos has a more complete data set on some of the tertiary channels. If you need old Twitter access CH will be your tool, if you want a bit more text on the more obscure channels then you’ll lean towards Sysomos.

Spam Filtering

Spam is the Achilles heel of social listening in the healthcare and pharmaceuticals space. There is so much of it that sometimes a third of our analysis time is spent cleaning the data set to try and get legitimate results and even then they are directional because you never know when that spike in mentions is going to turn out to be a river of “no prescription needed” spam.

The analysts typically end up with funny looking queries that feature spam reduction expressions like this:

AND NOT (cialis OR outlet OR pharmacie OR tramadol OR goto=findpost OR “buy generic online”~5 OR viagra OR “purchase online”~5 OR “without prescription”~3 OR mastercard OR echeck OR AMEX OR cod OR fedex OR pharmacie OR guitton OR tiffany OR “no prescription needed” OR “without prescription”~4 OR “online order”~5 OR site:lifenet-sy.com)

And all of the above is for one project only. Each project has its own collection of spammers and requires its own custom filtering.

Winner: Crimson Hexagon

My sense is that Crimson Hexagon does a better job at eliminating spam before it gets to the user’s view. When we look at the different dashboards using identical queries we find that the tools have:

Sysomos: 2.7 million posts over 12 months

Crimson Hexagon: 2.0 million posts over 12 months

This is also where the Crimson Hexagon training shows its strength, but more on that in a bit.

Operation

There are some similarities and some differences between Sysomos and Crimson Hexagon in how they approach the tasks of social listening.

Sysomos

Sysomos is the simplest model to get your head around. There’s a giant database of posts against which the analyst can write queries and get results in real-time. The usage pattern is pretty simple:

Write query

Analyze results and pull learnings

Revise query

Repeat

The dashboard shows the highest level of this data. Here is an example for migraine keywords:

Crimson Hexagon

The way that CH works is that the analyst sets up a “Monitor” using a query similar to the one we would use on Sysomos. This Monitor then gets compiled and, once complete, the analyst can interact with the data is a very fluid way.

Crimson Hexagon home page

For example, the trendline across the top of the screen (1) is interactive and the analyst can just drag and drop to choose the time frame for any report with very little lag.

Training Day

Monitors get trained using a special tool where analysts will bucket found posts into categories that they define. The tool will then take these posts and use Bayesian logic (I think) to then categorize the rest of the data. This could be a fantastic way to organize posts in a Monitor and when an analyst is using the same data set over a long period of time could really add value.

There is an art to the proper selection of posts, however, and I didn’t really get there over the course of this test. I had access to the tool for a month but let’s face it, Klick Health is a busy agency so I only really used the tool for five or six sessions.

The configuration can take hours and the build time for a Monitor can also be hours, so the analyst can find that setup takes a long time. In our agency we often need to jump from topic to topic very quickly so CH may be better suited to longer engagements where analysts are dedicated to a brand over months and years.

The Winner: Sysomos

As an agency that needs to jump in and pull data for any condition, brand, or company at any time the direct access afforded by Sysomos is hard to beat.

Full disclosure on Sysomos

During much of 2014 the system had significant performance “challenges.” In fact it was these performance issues that made me look around for other solutions such as Crimson Hexagon. However, at the end of 2014 Sysomos had completed a migration to a new back end technical architecture (I don’t know the details) and stability and performance returned to acceptable levels.

Every time the analyst presses “Analyze Now” the system is essentially running a new query against the full database so there can still be delays but screens update now in seconds rather than minutes so usage of the system is again fluid and natural.

Reporting on the Data

The two systems have very different reporting tools. The Crimson Hexagon suite of tools feels a lot tighter and integrated than the Sysomos set.

Sysomos

With Sysomos we find a wide variation in what you can do on different platforms such as Blogs, Twitter, Facebook, etc. Blogs have the most tools, followed by Twitter, and then the rest of the channels which have a variety depending on how much time Sysomos has put in and how easy the data is to work with.

Aesthetically the charts may not be as beautiful as other tools such as Radian 6 and Crimson Hexagon, but they get the job done and show the analyst what they need to know.

Sysomos trend chart

Sysomos buzzgraph

Sysomos geography

So, they’re not beautiful, but they render relatively quickly (now) and they convey important information in a clear way to the analyst.

Crimson Hexagon

The interactive tools packaged in Crimson Hexagon are a joy to use. They are full of fun interactions that surprise and delight the analyst. The visualizations are well designed and they convey good data.

Crimson Hexagon topic wheel

Crimson Hexagon topic clusters

Crimson Hexagon geography

But… I find that CH can be a bit more difficult to “dive in” to the underlying data and then quickly pull back to the overview. Like the setup issues I had this may be related to my relative lack of experience with the tool but Sysomos just felt like I was always “closer to the metal” than with CH.

The Winner: Sysomos

From where I sit, both tools provide very good insight into what populations of people are saying on social channels but in the end the more direct level of control I get with Sysomos is more important than the superior user friendliness of Crimson Hexagon.

Summary

So, both of these tools are great solutions for investigating topics on social media and teasing out the themes that patients are discussing. My analysis ended up like this:

Topic

Sysomos

Crimson Hexagon

Data

Tie

Tie

Spam Filtering

Winner

Operation

Winner

Reporting

Winner

It was a close and hard fought contest, but for now we’re still leaning towards Sysomos.

When a user searches for one of the 400 top health conditions, as defined by search volume, the Knowledge Graph appears in Google’s search engine results page (SERP) on the right hand side. Its intent is to be a one-stop, easy to read overview of the specific health condition, including symptoms and treatment information.

We worked with a team of medical doctors (led by our own Dr. Kapil Parakh, M.D., MPH, Ph.D.) to carefully compile, curate, and review this information. All of the gathered facts represent real-life clinical knowledge from these doctors and high-quality medical sources across the web, and the information has been checked by medical doctors at Google and the Mayo Clinic for accuracy.

Notes on the Google Knowledge Graph

This isn’t Google’s first foray into healthcare information. Google Health did not catch on as hoped and was discontinued in 2012. Although currently the Health Knowledge Graph (KG) only appears for the top 400 top-level condition searches, how and when this initiative may expand is unknown at this time and will depend on how it is received.

How does it affect our advertisers’ media?

As with most things in life, there is a pro and a con. With most advertising dollars spent on an impression or click the KG could help prequalify who you are paying for; meaning the person may have absorbed very high level info from the Knowledge Graph and is now able to decide if they should actually go further to get more information. This is a positive as educating a user in the healthcare space is a key challenge.

Is there a con? Not necessarily, but there will be a challenge for advertisers to direct their traffic to deeper and more actionable information with their advertising.

Within the search results, where this knowledge graph appears, we utilize three key areas:

Paid search listings

Organic search listing for advertisers sites

Display placements within key sites, such as WebMD, that frequently rank high within the organic search listings

For paid search, in order to not “lose” real estate, we should focus more on long tail search queries and key terms with modifiers and less on the general condition search terms.

For example, we would focus less on ‘multiple sclerosis’ and more on ‘multiple sclerosis treatment’, ‘ms medications’, and ‘multiple sclerosis diagnosis’.

This does not mean we avoid the “root” terms, but we need to make sure that by using “root” terms that we are driving traffic to more information than the Knowledge Graph can provide to keep users engaged.

This also means that our long tail or modified terms need to match what the user queries in order to drive them to the most relevant page on an advertisers’ site.

In mobile, the Knowledge Graph may have more of an impact as it will be pushing all ads and organic further down the page on an already small screen. For users who are looking for instant gratification, they may use the Knowledge Graph as their source and ignore results further down the page.

The Knowledge Graph will most likely result in a change in targeting methods to focus on treatments, medications, and the like, instead of the affliction or condition itself.

From an SEO perspective, the same logic around targeting that applies to paid search holds true: do not optimize on broad condition searches but focus on searches that answer specific questions. This may actually help searchers discover a drug of which they were unaware (drug names appear in the Treatment tab), and may lead to further research that may result in organic traffic to a brand website.

In terms of display, the logic again is fairly similar. In most cases, the patients who advertisers wish to target should be past the point at which they’re looking for symptoms and treatments. Rather, they are searching for resources in which to manage their disease. Patients will not be able to find this info in the Knowledge Graph therefore they must dig deeper into other sites. Again, this should prove to be beneficial to publishers and advertisers as we will be reaching a better qualified audience.

The Authors

This POV was created by three members of the Klick Health Media team:

Bill Lawson, Media Manager

Sharon Virtue, Search Strategy Lead

Matt Hogan, SEM Manager

Download PDF

]]>http://www.klick.com/health/news/blog/sem-media/the-google-knowledge-graph-and-health-conditions/feed/0CMO survey dissected for healthcare / pharmaceuticalshttp://www.klick.com/health/news/blog/insights/cmo-survey-dissected-for-healthcare-pharmaceuticals/
http://www.klick.com/health/news/blog/insights/cmo-survey-dissected-for-healthcare-pharmaceuticals/#commentsWed, 25 Feb 2015 21:16:01 +0000http://www.klick.com/health/?p=369953The CMO Survey from Duke’s Fuqua School of Business allows us to do just that. The overview documents are interesting, but they also supply a raw data deck that breaks out “Healthcare and Pharmaceutical” CMO answers. The “n” values are low, of course, it looks like there were 16 CMOs in this category from a total of 288 survey responders. You can download the full reports, but we’re going to highlight just the healthcare data:

Digital marketing spend is set to increase 19.2% over the next 12 months, higher than the average of 14.7%

Mobile marketing spend is set to quadruple from 2.2% to 9.3% in the next 12 months, average is 3.2% to 9.0%

Social media accounts for 9.6% of companies’ marketing spend, essentially the same as the average at 9.6%

Social media is expected to rise to 16.7% of marketing budgets in 12 months, a faster rise than the average at 13.5%

Social media is expected to rise to 28.5% of marketing budgets in five years, a faster rise than the average at 22.4%

Social ROI is difficult to measure, 12.5% say they have proven it quantitatively, 37.5% say they have qualitative evidence of impact, and 50% say they have not yet been able to measure it, compared to 13.2%, 41.8%, and 45.0% respectively

Analytics is currently at 7.2% of marketing budgets, and expected to rise to 15.0% in three years

Also, 42.9% of CMOs say the pressure to prove the value of marketing is increasing, 57.1% say it’s staying the same, no one thinks it is decreasing.

The material is presented in aggregate, so it doesn’t look like the reports need to be sent to the Pharmacovigilance group for AE reporting. The sample screen shot shows the side effects, but we’re hoping that other data such as efficacy ratings is also included in the tool.

What PatientsLikeMe looks to get from the deal is embedded in this quote from their EVP of Marketing:

“We want to help patients wherever they are, so they can be better informed about the treatments they’re taking and make more informed health decisions,” said PatientsLikeMe Executive Vice President of Marketing and Patient Advocacy Michael Evers. “We’re thrilled to be working with the nation’s largest drugstore chain. Our work with Walgreens will give their patients important insights from people taking both simple and complex medications. It can also help enrich our treatment data should Walgreens patients decide to join our community.”

“Every time a patient comes in to the clinic or sees physicians on the wards, there’s a certain expectation of how their physician will dress,” says Petrilli. The data overwhelmingly suggests that first impressions do matter, though Petrilli and his colleagues find that patients are less concerned with attire after the first visit.

For healthcare marketers crafting messages online it seems like patients want physicians they can trust. Stock photography probably isn’t the best place to get these images, and make sure that your shots have your physicians dressed in their clinical best.

]]>http://www.klick.com/health/news/blog/insights/patients-more-compliant-for-professionally-dressed-physicians/feed/0Epic to open its own app storehttp://www.klick.com/health/news/blog/strategy/epic-to-open-its-own-app-store/
http://www.klick.com/health/news/blog/strategy/epic-to-open-its-own-app-store/#commentsWed, 25 Feb 2015 21:10:45 +0000http://www.klick.com/health/?p=369943

Mark Bakken, co-founder and former chief executive of Nordic Consulting … said the app store will launch in a few weeks and it will “open the floodgates” for all sorts of companies to develop and market their apps, especially those in the Madison area populated by former Epic employees.

The system is currently dubbed the “App Exchange” and is reported to work similarly to the Apple App Store in that developers submit their applications for review and approval. This review process should allow Epic to control the quality of apps that are endorsed, it remains to be seen if Epic will control the types of applications to protect its own business.

When we think of “app stores” we think of the Apple and Google mobile-focused stores that allow for apps to be downloaded on those devices. In this case the “Application Exchange” will likely be populated mostly with desktop tools that will allow provider networks extract more value from their Epic systems. The large Epic integrators will most likely be the first in the system with tools that they have custom-built for previous clients.

What it means

Healthcare marketers should take note of this development. While Epic, and other EHR vendors, typically do not welcome pharma involvement so they can be perceived as remaining unbiased third-party application developers may be more welcoming of information and content for drug education materials.

Ms. Wojcicki [23andMe founder] declined to say when 23andMe would start offering health information again, but said it would probably be this year. However, it would most likely be limited to a suite of carrier tests. “We want to be back on the market with meaningful information as soon as possible,” she said. [NYT interview]

The FDA for its part made clear in its press release that it has no problem with direct-to-consumer DNA testing in general:

“The FDA believes that in many circumstances it is not necessary for consumers to go through a licensed practitioner to have direct access to their personal genetic information. Today’s authorization and accompanying classification, along with FDA’s intent to exempt these devices from FDA premarket review, supports innovation and will ultimately benefit consumers,” said Alberto Gutierrez, Ph.D., director of the Office of In Vitro Diagnostics and Radiological Health in the FDA’s Center for Devices and Radiological Health. “These tests have the potential to provide people with information about possible mutations in their genes that could be passed on to their children.”

“I don’t have a Fitbit yet, but I work out hard,” he told Swisher. “Word is these Apple Watches might be a good companion for my workouts. So I’m gonna see, I’m gonna test it out.” Obama continued: “I don’t want to give Tim Cook too big of a plug here until I’ve actually seen the product, but he tells me it’s pretty good.”

We’ll be looking for a review after April rolls around, mister President.